Kulukeskeisyys

Kulukeskeisyys, also known as centrality in English, is a concept in network theory and graph theory that refers to the relative importance of a node (or vertex) within a network. It is a measure of how central or important a node is in terms of its connections to other nodes. There are several types of centrality measures, each providing a different perspective on a node's importance.

Degree centrality is the simplest measure, calculated as the number of direct connections a node has. Nodes with high degree centrality are often considered influential because they have many direct ties to other nodes.

Closeness centrality measures how close a node is to all other nodes in the network. It is calculated as the reciprocal of the sum of the shortest path distances from the node to all other nodes. Nodes with high closeness centrality are often considered important because they can quickly interact with all other nodes.

Betweenness centrality measures the extent to which a node lies on the shortest paths between other nodes. It is calculated as the number of shortest paths that pass through the node. Nodes with high betweenness centrality are often considered important because they act as bridges or gatekeepers in the network.

Eigenvector centrality, also known as Google's PageRank, measures the influence of a node based on the influence of its neighbors. It is calculated as a function of the centralities of the nodes to which it is connected. Nodes with high eigenvector centrality are often considered important because they are connected to other important nodes.

Kulukeskeisyys is a fundamental concept in network analysis, used in various fields such as social network analysis, biology, and computer science. It helps to identify key nodes in a network, understand the structure of the network, and predict the spread of information or influence within the network.